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Open AccessArticle

Genome Insights into the Novel Species Microvirga brassicacearum, a Rapeseed Endophyte with Biotechnological Potential

1
Microbiology and Genetics Department, University of Salamanca, 37007 Salamanca, Spain
2
Spanish-Portuguese Institute for Agricultural Research (CIALE), Villamayor, 37185 Salamanca, Spain
3
Associated R&D Unit, USAL-CSIC (IRNASA), 37007 Salamanca, Spain
4
Institute of Natural Resourses and Agrobiology of Salamanca (IRNASA-CSIC), Salamanca 37008, Spain
*
Author to whom correspondence should be addressed.
Microorganisms 2019, 7(9), 354; https://doi.org/10.3390/microorganisms7090354
Received: 30 June 2019 / Revised: 2 September 2019 / Accepted: 6 September 2019 / Published: 14 September 2019
(This article belongs to the Special Issue Plant Microbial Interactions)

Abstract

Plants harbor a diversity of microorganisms constituting the plant microbiome. Many bioinoculants for agricultural crops have been isolated from plants. Nevertheless, plants are an underexplored niche for the isolation of microorganisms with other biotechnological applications. As a part of a collection of canola endophytes, we isolated strain CDVBN77T. Its genome sequence shows not only plant growth-promoting (PGP) mechanisms, but also genetic machinery to produce secondary metabolites, with potential applications in the pharmaceutical industry, and to synthesize hydrolytic enzymes, with potential applications in biomass degradation industries. Phylogenetic analysis of the 16S rRNA gene of strain CDVBN77T shows that it belongs to the genus Microvirga, its closest related species being M. aerophila DSM 21344T (97.64% similarity) and M. flavescens c27j1T (97.50% similarity). It contains ubiquinone 10 as the predominant quinone, C19:0 cycloω8c and summed feature 8 as the major fatty acids, and phosphatidylcholine and phosphatidylethanolamine as the most abundant polar lipids. Its genomic DNA G+C content is 62.3 (mol %). Based on phylogenetic, chemotaxonomic, and phenotypic analyses, we suggest the classification of strain CDVBN77T within a new species of the genus Microvirga and propose the name Microvirga brassicacearum sp. nov. (type strain CDVBN77T = CECT 9905T = LMG 31419T).
Keywords: plant–bacteria interactions; genome mining; PGPB; biofertilizer; CAZymes; secondary metabolites; hydrolytic enzymes plant–bacteria interactions; genome mining; PGPB; biofertilizer; CAZymes; secondary metabolites; hydrolytic enzymes

1. Introduction

After millions of years of evolution, microorganisms have compiled a noteworthy genetic diversity with biotechnological potential, which can be additionally enhanced by tools, such as genetic engineering or heterologous gene expression. Thus, microbial isolates are essential for diverse biotechnology-based industries, such as pharmaceutical biotechnology (where they play important roles in the production of antibiotics, antivirals, anticarcinogenic compounds, etc.), agricultural biotechnology (where they are applied as biocontrol agents or probiotics for plant growth promotion), and environmental biotechnology (with variate applications such as lignocellulose breakdown or degradation of xenobiotic compounds). Moreover, according to recent estimations, potentially 99.999% of microbial taxa remain undiscovered [1], so there is a huge genetic potential yet undiscovered.
In the last couple of decades, the extensive use of the PCR and sequencing of the 16S rRNA gene has allowed a more accurate bacterial identification and served as the base for the discovery of new taxa, being the gold standard for prokaryote identification. According to Jongsik and collaborators [2], a bacterial strain with a similarity under 98.7% in the 16S rRNA gene sequence with the type strain of its closest related species represents a novel species and, in case of a similarity over 98.7%, a value under 70% in total DNA–DNA hybridization (DDH) also indicates a novel species [3]. More recently, the quick development of DNA sequencing platforms that generate rapid and low-cost high-throughput sequencing data has spearheaded the widespread sequencing of bacterial genomes which, together with the development of bioinformatics tools for genome sequence comparisons, facilitates the process of new species identification, by means of genome-to-genome sequence comparison [2].
Genome sequences also allow us to mine the genetic potential of a microorganism for different purposes, for example, plant growth promotion mechanisms [4] and the production of secondary metabolites with applications in the pharmaceutical industry [5] or carbohydrate-active enzymes (CAZymes) with several biotechnologically based industry uses, such as biomass degradation, biodiesel production, or bioremediation [6].
Plants are the ecological niche of a broad range of microorganisms which constitute their microbiome [7]. Some of these microorganisms establish symbiotic associations with the plant, supplying their host with nutrients or improving its fitness by the production of phytohormones or the induction of resistance to abiotic stresses [8]. These plant growth-promoting (PGP) microorganisms can be applied as biofertilizers or plant probiotics to improve crop yields in an ecologically friendly manner and thus, they are produced and formulated as bioinoculants in the industry. Nevertheless, plants are an underexplored niche as a source of microorganisms for other biotechnological applications different from those of the agro-based industry.
The genus Microvirga is a cosmopolitan genus which as of now includes 17 validated species isolated from a wide diversity of niches, such as human stool [9], air [10], thermal water [11], natural, domestic, and contaminated soils [12,13,14,15,16,17], and even as legume nodule endophytes [18,19,20]. Some studies report the genetic potential of some strains classified within the Microvirga genus for arsenic oxidation [15] and the production of pigments and amylolytic enzymes [21].
In this study, we propose the description of Microvirga brassicacearum sp. nov. isolated as a rapeseed bacterial endophyte with the capability to promote plant growth. Moreover, we obtained and mined the genome sequence of strain M. brassicacearum CDVBN77T, showing its genetic potential not only as a plant growth promoter but also as a producer of secondary metabolites with a potential interest in the pharmaceutical industry as well as of enzymatic machinery for biomass degradation.

2. Materials and Methods

2.1. Strain Isolation and Identification

Strain CDVBN77T was isolated as part of a collection of rapeseed bacterial root endophytes from the roots of rapeseed plants harvested in the locality of Castellanos de Villiquera (province of Salamanca, Spain) [22]. Plants in the phenological state of rosette were collected and kept refrigerated to be transported to the lab. Root endophytes were obtained after washing with sterile water. The plants were extracted from the soils, kept refrigerated, and shipped to the laboratory. To isolate rapeseed root bacterial endophytes, roots were washed in sterile Petri dishes containing sterile water (10 times) and then sterilized by immersion in sodium hypochlorite (2%) for 2 min. Afterward, surfaced sterilized roots were washed in sterile water (5 times) and dried without using sterile filter paper.
Surface sterilized roots were smashed with a pestle in a sterile mortar and the extract was serially diluted in sterile water. Then, 100 µL of the 10−2, 10−3, and 10−4 dilutions were plated onto Petri dishes containing different media: YMA (Microkit®, Laboratorios Microkit, Madrid, Spain), Tryptic Soy Agar (TSA) (DifcoTM, Difco Laboratories, Le Pont de Claix, France), 869 medium (Tryptone (10 g/L), yeast extract (5 g/L), NaCl (5 g/L), D-glucose (1 g/L), CaCl2 (0.345 g/L), and agar (20 g/L)), and ten times diluted 869 medium (869(1/10) medium). Plates were incubated at 28 °C for 21 days. The emerging bacterial colonies were regularly isolated to obtain pure cultures. Then, for long-term storage, isolated strains were stored in a sterile 20% glycerol solution at −80 °C.

2.2. DNA Extraction and 16S rRNA Amplification and Sequencing

CDVBN77T DNA for amplifying and sequencing 16S rRNA gen was extracted using the REDExtract-n-AmpTM Plant PCR Kit (Sigma-Aldrich, Darmstadt, Germany) following the manufacturer’s instructions. The amplification was performed using 2 µL of bacterial DNA (100 µg/mL) as the template, 6 µL of Milli-Q sterile water, 12.5 µL REDExtract Ready Mix, 2.5 µL 27F 1 µM (5’ GAGGGTGGCGGTTCT 3’), and 2,5 µL 1522R 1 µM (5’AAGGAGGTGATCCANCCRCA 3’). The PCR conditions were the following: a first step of pre-heating at 95 °C for 9 min, 35 cycles of denaturing at 94 °C for 1 min; annealing at 56.5 °C for 1 min 30 s and extension 72 °C for 2 min, and a final extension at 72 °C for 7 min.
PCR product was purified using DNA Cleanup Micro Kit (Thermo ScientificTM, Göteborg, Sweden). The sequence reaction was performed on an ABI PRISM sequencer (Applied BiosystemTM, Foster, CA, USA) using a Dye Terminator Cycle Sequencing Ready Reaction Kit (University of Salamanca, Salamanca, Spain). The isolate strain was identified using the following databases: NCBI’s BLASTn program [23] (https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastSearch) and EzTaxon tool [24].

2.3. Draft Genome Sequencing and Annotation

Bacterial DNA for genome sequencing was obtained from cells grown in YMA medium at 28 °C for five days. DNA extraction was performed with the Quick DNATM Fungal/Bacterial Miniprep Kit (Zymo Research®, Irvine, CA, USA) following the protocol provided by the manufacturer.
The draft genome sequence was obtained on an Illumina platform from the Genomics Service of the Institute of Functional Biology and Genomics (IBFG) (Salamanca, Spain). Sequences were assembled using Velvet 1.12.10, [25]. Gene calling, annotation, and search of genes related to plant growth promotion capabilities were performed using RAST Pipeline [26]; the BlastKOALA tool was also used to perform KEGG Orthology (KO) assignment based on the KEGG database [27] in order to complete the mining of genes related to plant growth promotion; the dbCAN2 meta server [28] was used to identify the coding sequences (CDSs) encoding carbohydrate-active enzymes (CAZymes) using HMMER annotation; and the analysis of gene clusters related to secondary metabolites production was performed using antiSMASH 5.0 webserver [29]. This genome sequence was deposited at the DDBJ/EMBL/GenBank under the accession VCMV00000000. The version described in this paper is version VCMV01000000.

2.4. Genotypic Analysis of Microvirga brassicacearum CDVBN77T

The GenBank accession number of the CDVBN77T 16S rRNA gene sequence is MK938302. Phylogenetic analysis of the CDVBN77T 16S rRNA gene sequence and the sequences of the type strains of all the species included within the genus Microvirga was performed using MEGA7 software [30], based on the alignment of the sequences with Clustal_W [31]. The distances were calculated using Kimura’s two-parameter model [32], and the phylogenetic tree was inferred using neighbor-joining (NJ; [33]) analysis. The average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) values between the draft genome sequence of strain CDVBN77T and those of its closest related species M. aerophila c27j1T (GenBank/EMBL/DDBJ accession number NZ_QOIO00000000.1) and M. flavescens DSM 21344T (GenBank/EMBL/DDBJ accession number QMKH00000000) were calculated using the ANI calculator (www.ezbiocloud.net/tools/ani) and the Genome-to-Genome Distance Calculator (GGDC 2.1) (http://ggdc.dsmz.de/distcalc2.php), respectively. The mol % G+C content of DNA was determined from the draft genome sequence.

2.5. Chemotaxonomic Analysis of Microvirga brassicacearum CDVBN77T

For the analysis of fatty acid methyl esters (FAMEs), biomass was harvested as detailed by Weon et al. [8]. For the analyses of polar lipids and respiratory quinones, biomass was harvested after cultivation of the bacterium for seven days in R2A broth medium (dextrose (0.5 g/L), dipotassium phosphate (0.3 g/L), casamino acids (0.5 g/L), magnesium sulphate (0.05 g/L), proteose peptone (0.5 g/L), sodium pyruvate (0.3 g/L), starch (0.5 g/L), and yeast extract (0.5 g/L)) at 28 °C and 150 rpm shaking. Analysis of FAMEs was performed as previously described [34]. For the identification of polar lipids and respiratory quinones, cells collected from the plates into sterile Falcon® tubes were freeze dried and sent to the Identification Service of the German Collection of Microorganisms and Cell Cultures DSMZ.

2.6. Microvirga brassicacearum CDVBN77T Bacterial Characterization

Catalase and oxidase tests [35] and Gram staining [36] were performed using previously described protocols.
Cell morphology and flagella were observed under a Zeiss EM209 transmission electron microscope, after growth in YMA medium at 28 °C for five days and cell treatment with 2% uranyl. To assay salt tolerance, the bacterium was cultivated in YMB medium (mannitol (7.0 g/l), yeast extract (2 g/l), dipotassium phosphate (0.2g/l), and magnesium sulphate (0.2g/l)) supplemented with 0, 0.5, 1, 1.5, and 2% (w/v) NaCl. The same medium adjusted to a final pH range of 3–11 was used to examine the growth capability at different pHs; in both cases, flasks containing 50 mL of the different media were inoculated with a 10 µl sterile plastic loop containing cells collected from a two-day plate culture of the bacterium. After the inoculation, flasks were cultivated in a shaker at 150 rpm for two days at 28 °C. Plates containing YMA medium (YMB plus 2% agar) were incubated at 4, 12, 25 and 37 °C to determine the temperature range for optimal growth. In all cases, the cultures were examined at 2, 5, 10, and 15 days after inoculation.
Enzymatic assays were performed using the p-nitrophenyl (pNP) substrates listed in Table 1. Substrates were used at a concentration of 0.2% in 50 mM phosphate buffer (pH 7); however, those requiring pH 8.5 were prepared in Tris-HCl 0.2 M buffer and those requiring pH 5.0 were prepared in an acetate buffer (0.2 M). The enzymatic reactions were carried out in a multi-well plate mixing 50 μL of substrate prepared as specified above and 50 μL of a suspension of bacteria in sterile water with 6 × 109 CFU/mL obtained from cells previously grown in YMA medium for 15 days at 28 °C. Plates with the reaction mixture were incubated at 28 °C for 24 h and then revealed with 100 μL per well of a 4% sodium carbonate solution. A positive reaction was evidenced by the appearance of a yellow color within a few seconds.
To evaluate siderophore production, strain CDVBN77T was inoculated in M9-CAS-agar medium plates [37] with the modifications suggested by Alexander and Zuberer [38] after 21 days of growth at 28 °C. The addition of hexadecyltrimethylammonium bromide (HDTMA) as a cationic solvent was used to stabilize the Fe-CAS complex, which provides the characteristic orange-colored halo around the colonies when siderophores are produced.
The solubilization of non-soluble phosphates into soluble assimilable ions was analyzed in Pikovskaya medium plates [39], which contain calcium phosphate (Ca2HPO4) as P source. The presence of clear halos surrounding bacterial colonies are indicative of phosphate solubilization. Strain CDVBN77T was inoculated in Pikovskaya medium and phosphate solubilization was evaluated after 21 days of growth at 28 °C.
Cellulose production was determined as described by Robledo et al. [40] in Nutrient Agar (NA) plates containing Congo Red colorant, which binds to cellulose polymers. Red-colored colonies are indicative of cellulose production. Strain CDVBN77T was inoculated in plates with Congo Red and the color of the colonies was evaluated after 21 days of growth at 28 °C.
Other phenotypic characters were tested by using the API 20NE and API ZYM (bioMerieux®) miniaturized galleries following the manufacturer’s instructions.

3. Results

3.1. Bacterial Isolation and Identification

Strain CDVBN77T was isolated as part of a collection of rapeseed root endophytes from plants sampled at the municipality of Castellanos de Villiquera (province of Salamanca, Spain) [22]. The comparison of the 16S rRNA gene sequence with those of type strains of described species available in GenBank and EzBiocloud databases showed that all strains but CDVBN77T showed similarities higher than 98% with their closest related type strains, whereas the similarity of strain CDVBN77T with M. aerophila DSM 21344T, its closest related type strain, was only 97.64%, which according to the threshold value of 98.7% in the 16S rRNA gene sequence with the closest related species indicated by Jongsik and collaborators [2] indicates that the strain constitutes a new species within the genus Microvirga.
Therefore, we performed a phylogenetic analysis of the 16S rRNA gene sequence of strain CDVBN77T and those of the type strains of all species included within the genus Microvirga.
Phylogenetic trees constructed with both Maximum Likelihood (ML) and Neighbor Joining (NJ) methods showed a similar topology (Figure 1) with strain CDVBN77T appearing in a separated branch with M. flavescens c27j1T and M. aerophila DSM 21344T as the closest related species. Thus, the phylogenetic analysis of the 16S rRNA gene supports the classification of the bacterium CDVBN77T as a new species within the genus Microvirga.

3.2. Genome Properties and Comparison with Those of Its Closest Related Species

The genome sequence of strain CDVBN77T was obtained in order to be compared with those of its closest related species. Genome properties of the strain based on RAST annotations are detailed in Table 2.
ANI values between the genome sequence of CDVBN77T and M. flavenscens c27j1T and M. aerophila DSM 21344T were 76.14% and 77.23%, respectively. Considering the recommended ANI threshold value for species delimitation of 95% to 96% [41], these genome comparisons clearly support the classification of strain CDVBN77T as a novel species of the genus Microvirga.
The results of dDDH between the genome sequence of CDVBN77T and M. flavescens c27j1T and M. aerophila DSM 21344T were 20.50% and 21.20%, respectively. Since the dDDH threshold value for species delineation has been established at 70% [42], we can conclude that the bacterial isolate CDVBN77T does not belong to its closest related species and should be classified within a new species of the genus Microvirga.

3.3. Plant Growth Promotion Potential

The genome mining revealed many genes involved in PGP mechanisms. Regarding the acquisition of nutrients, we found some mechanisms involved in the solubilization of P and K, making their uptake easier for the plant. The genome annotations showed genes encoding for proteins with phosphatase activity, one of the main mechanisms for P solubilization, such as the enzymes alkaline phosphatase (EC 3.1.3.1), exopolyphosphatase (EC 3.6.1.11), inorganic triphosphatase (EC 3.6.1.25) and pyrophosphatase (EC 3.6.1.1), polyphosphate kinase (EC 2.7.4.1), and a pyrophosphate-energized proton pump (EC 3.6.1.1) [43]. The glucose dehydrogenase PQQ-dependent enzyme (EC 1.1.5.2), which is responsible of the oxidation of glucose into the phosphate solubilizing molecule gluconic acid [44,45], was also found in this search. In addition, some other enzymes involved in the production of P and K solubilization acids are encoded by this bacterium, such as citrate synthase (EC 2.3.3.1) and malate synthase G (EC 2.3.3.9) [46]. Moreover, regarding the transport of these two elements, the genome encodes transport systems such as the Pst system for P [47] or the Kup and Kef systems for K [48]. Regarding the iron supply, we found some genes annotated as siderophores or other iron-associated transport proteins, such as the ferrichrome-iron receptor, a ferric iron ABC transporter, a ferric hydroxamate ABC transporter (TC 3.A.1.14.3), the ATP-binding protein FhuC, as well as proteins of the Fec system, the AfuABC system (Iron (III)), and the SitA system (Iron(II)/manganese). Finally, the capability to fix atmospheric nitrogen into a plant’s available state of nitrogen [49] is a common mechanism in rhizobial strains. In this case, we found the presence of genes implicated on Fix and Nif systems.
A prior step to endophytic living is to attach and form biofilms over the root surface. Bacteria commonly produce exopolysaccharides in order to colonize the root surface [50]. Genome annotations revealed a great number of genes related to the synthesis or transport of exopolysaccharides, for example, the exoD gene, which is associated with this process [51], lpx genes, responsible for the synthesis of this type of molecules [52], or lpt [53] and Rf [54] transport systems. Once inside the plant, the bacterium must evade the plant defense. The genome annotations revealed that the bacterium encodes genes for the production of salicylate 1-hydroxylase (EC 1.14.13.1), an enzyme that degrades the salicylic acid into catechol.
Moreover, strain CDVBN77T grew on chrome azurol S (CAS) indicator medium, where the colonies were surrounded by a yellow-orange halo (2 mm radius around colonies), indicating siderophore production.
In addition, CDVBN77T solubilized phosphate on Pikovskaya’s agar, forming halos around its colonies (2 mm radius around colonies). Additionally, the results obtained using pNP-based substrates showed the production of phosphatases (with activity at acid, alkaline, and neutral pH) and bisphosphatases (with activity at alkaline pH).
Furthermore, strain CDVBN77T colonies were red after seven days of incubation on plates containing Congo Red. The intensity of the color was comparable to that recorded for other strains, which indicated that CDVBN77T produces a moderate amount of a polysaccharide with 1,4-β-glycosidic bonds.

3.4. Potential for the Production of Enzymes with Biotechnological Potential

Analysis of the genome sequence of strain M. brassicacearum CDVBN77T with dbCAN2 showed 115 genes encoding different CAZymes involved in degradation, modification, or creation of glycosidic bonds.
In summary, we identified gene modules belonging to five different enzyme classes: (i) glycoside hydrolases (GHs), enzymes that catalyze the hydrolysis of glycosidic linkage of glucoside—30 gene counts in 15 different families; (ii) glycosyltransferases (GTs), involved in the formation of glycosidic bonds—46 gene counts in 11 different families; (iii) polysaccharide lyases (PLs), which perform non-hydrolytic cleavage of glycosidic bonds—2 gene counts in 2 different families; (iv) carbohydrate esterases (CEs), which hydrolyze carbohydrate esters—22 gene counts in 6 different families; and (v) auxiliary activities (AAs), redox enzymes that act in conjunction with CAZymes—15 gene counts in 5 different families (Table 3).
The main enzymes acting in the lignocellulosic breakdown are GH. GHs in the genome sequence of M. brassicacearum CDVBN77T belong to the families 1, 2, 3, 15, 16, 23, 25, 31, 63, 102, 103, 105, 108, 109, and 113. Regarding enzymes related to biomass hydrolysis, we found five genes belonging GH family 1, which includes among other enzymes β-glucosidases (EC 3.2.1.21), exoglucanases (EC 3.2.1.74), and 1,4-β-xylosidases (EC 3.2.1.37), two genes belonging to GH family 2, which includes α-L-arabinofuranosidases (EC 3.2.1.55) and 1,4- β-xylosidases (EC 3.2.1.37), and two genes belonging to GH family 3, which includes β-glucosidases (EC 3.2.1.21), exoglucanases (EC 3.2.1.74), 1,4-β-xylosidases (EC 3.2.1.37), and α-L-arabinofuranosidases (EC 3.2.1.55). The enzymes β-glucosidases (EC 3.2.1.21) and exoglucanases (EC 3.2.1.74) belong to the cellulase complex, and 1,4-β-xylosidases (EC 3.2.1.37) and α-L-arabinofuranosidases (EC 3.2.1.55) are implicated in hemicelluloses hydrolysis, cellulose and hemicelluloses being the most abundant plant polymers. β-glucosidases (EC 3.2.1.21) and 1,4-β-xylosidases (EC 3.2.1.37) appear annotated in RAST and BlastKOALA annotations of the CDVBN77T genome sequence. The presence of genes encoding these enzymes suggests that this bacterium could have biotechnological potential for the production of enzymes for lignocellulosic biomass breakdown.
Moreover, enzymatic assays based on pNP-based substrates show the capability of the strain to synthesize β-galactosidase, β-glucosidase, and α-rhamnosidase. Nevertheless, in the conditions assayed, we could not detect the production of xylosidases or arabinofuranosidases.

3.5. Genome Mining of Gene Clusters Associated to the Biosynthesis of Secondary Metabolites

AntiSMASH output revealed five biosynthetic gene clusters (BGCs) involved in the secondary metabolism of the bacterium.
One of those clusters encodes an undescribed terpene BGC in which the core gene is a phytoene synthase (EC 2.5.1.32), an enzyme involved in the first steps of the biosynthesis of carotenoids. According to antiSMASH clusterblast, this cluster seems to be distributed among different Ochrobactrum and Brucella genomes, but it does not appear in the seven genomes of strains belonging to the Microvirga genus included in the database at the moment of writing this work.
Another BGC found in Microvirga brassicacearum CDVBN77T is related to the synthesis of a N-acyl-homoserine lactone. This family of molecules is often involved in bacterial quorum sensing [55]. In this case, the cluster is present in other Microvirga genomes, but it has never been tested for the production of any specific molecule.
Microvirga brassicacearum CDVBN77T also encodes two nonribosomal peptide synthetases (NRPSs) BGCs that are neither described for the production of an already known molecule. Moreover, none of them share similitude with any region of any other Microvirga strains’ genomes, although it appears related to sequences of strains belonging to Pseudomonas and Chelatococcus genera (with 6%–20% genes showing similarity).
In addition, a type III polyketide synthase (T3PKS) is present, a type of BGC involved in the synthesis of a great diversity of molecules derived from the metabolism of fatty acids [56]. The region encoding this BGC shares certain similitude with regions of some Pseudomonas genomes but not in the core genes, and none of them has been described for the production of a known metabolite.

3.6. Colony and Cellular Morphology in Strain CDVBN77T

After seven days of incubation at 28 °C in R2A agar medium, strain CDVBN77T forms circular, flat, and transparent colonies with entire borders. The cells are rod-shaped, 1.2–1.5 µm in length and 0.7–0.9 µm in width, and motile by means of a polar flagellum (Figure 2).

3.7. Phenotypic and Chemotaxonomic Characterization of Strain CDVBN77T

The analysis of respiratory quinones revealed that ubiquinone-10 (Q-10) is the major quinone in CDVBN77T, and the main polar lipids of this strain are supporting the classification of the bacterium within the genus Microvirga [11].
The major fatty acids in strain CDVBN77T are C19:0 cyclo ω8c (24.3%) and Summed Feature 8 (39.3%) (Table 4), as it occurs for its closest related strains M. flavescens c27j1T [17] and M. aerophila DSM 21344T [10], as well as for the type species of the genus M. subterranea DSM 14364T [11], supporting the classification of the strain within the genus Microvirga. However, the fatty acid profile of this strain significantly differs from that of the closest related species (Table 4), supporting the classification of CDVBN77T into a different species within the genus.
Phenotypic features analyzed in strain CDVBN77T are detailed in the species protologue, and the main phenotypic differences with the closest related species and the type species of the genus are summarized in Table 5.

4. Discussion

Many plant endophytic strains have been described as new taxa [57,58,59,60]. In this study, we isolated strain CDVBN77T, whose 16S rRNA gene sequence showed a relatively low similarity with its closest related species, M. aerophila DSM 21344T (97.64%) and M. flavescens c27j1T (97.50%), which suggested that it could belong to a new species within the genus Microvirga. Several Microvirga species, namely, M. lupini, M. lotononidis, M. zambiensis, M. ossetica, and M. vignae [18,19,20], were for the first time isolated as legume endophytes. The phylogenetic analysis of this strain based on the 16S rRNA gene showed that the bacterium appears in a separated branch within the genus Microvirga but clustered with its two closest related type strains M. flavescens c27j1T and M. aerophila DSM 21344T. The presence of Q-10 as the major quinone and C19:0 cyclo ω8c and Summed Feature 8 as the main fatty acids supports its classification within the genus Microvirga. However, this isolate differs from the closest species, M. aerophila and M. flavescens, in the capability to hydrolyze gelatin and aesculin, positive for M. brassicacearum CDVBN77T and negative for the other two, and the color of the colonies in R2A agar medium, transparent in M. brassicacearum CDVBN77T and light yellow and pale pink in M. flavescens and M. aerophila, respectively. Unlike M. aerophila, it reduces nitrates to nitrites and assimilates D-glucose and L-arabinose, and it does not produce the enzyme β-glucoronidase; moreover, in contrast to M. flavescens, it produces trypsin. Thus, the results of the phylogenetic, chemotaxonomic, and phenotypic analysis clearly support the classification of strain CDVBN77T as a new species within the genus Microvirga, for which the name Microvirga brassicacearum sp. nov. is proposed.
The genus Microvirga belongs to Rhizobiales, a broadly studied order in the field of plant–bacteria interactions because of its role as plant growth promoter. Five species of the genus Microvirga have been described as plant endosymbionts capable of promoting plant growth, namely, M. lupini, M. lotononidis, M. zambiensis [18], M. vignae [20], and M. ossetica [19]. The genome mining of strain M. brassicacearum CDVBN77T shows the presence of genes implicated in the nutrient provision to the plant, such as P and Fe, capabilities also proven in in vitro tests, as well as K and N. Moreover, both the analysis of the genome sequence as well as in vitro tests show the capability of this strain to synthesize exopolysaccharides which may allow the attachment of the bacterial cells to the plant root surface in order to establish an interaction with the host.
To live as plant endophytes, bacteria must have genetic machinery to use plant-synthesized compounds as a source of nutrients. Some of the enzymes implicated in plant compound degradations are very interesting for industries based on biomass degradation, such as bioethanol production, pulp and paper industries, beverages industries, medicinal and analytical chemistry, fabrication of detergents, and textile de-sizing [6]. Thus, we explored the enzymatic machinery related to carbohydrate degradation encoded by the M. brassicacearum CDVBN77T genome. As a result, we identified genes related to the degradation and modification of biomass polymers, such as cellulose and hemicelluloses. β-glucosidase is the key enzyme in the cellulase system [34,61,62], since it converts cellobiose to glucose, completing the final step during cellulose hydrolysis. In the genome of M. brassicacearum CDVBN77T, we have found five genes belonging to family GH1 and three genes belonging to family GH3; both enzyme families include enzymes, such as β-glucosidases (EC 3.2.1.21) or even exoglucanases (EC 3.2.1.74), enzymes which are also involved in the cellulose polymer degradation [63].
The complete degradation of hemicelluloses requires the combined activity of xylanases, β-xylosidases, and several accessory enzymes such as α-arabinofuranosidases [64]. In the genome of Microvirga brassicacearum CDVBN77T, we have found gene counts in the GH1, GH2, and GH3 families, all of them including enzymes with xylan 1,4-β-xylosidase (EC 3.2.1.37) activity. Moreover, GH2 and G3 families include enzymes with α-arabinofuranosidase activity. However, we could not detect the in vitro synthesis of xylosidases and arabinofuranosidases, either because the annotated genes belonging to the GH1, GH2, and GH3 families have other different activities, or because they were not induced under the assayed conditions.
On the other hand, we found how this bacterium is able to hydrolyze several substrates linked to p-nitrophenol, which reveals that the bacterium synthesizes α-rhamnosidase, with potential applications in the clarification and debittering of citrus juices, the enhancement of wine aromas, or the synthesis of certain pharmaceutical compounds [65] and β-galactosidase, with potential application in food processing industries for the hydrolysis of lactose in milk and milk by-products [66].
Regarding the secondary metabolism prospection of the bacterium, we found an interesting niche for researching secondary metabolite BGCs that have not been very studied within the Microvirga genus. AntiSMASH results showed that the CDVBN77T strain has the potential to encode at least five undescribed secondary metabolites; amongst those, a terpene, a PKS, and two NRPS have potential applications in industry. NRPS are widely distributed among many taxa, and their products, nonribosomal peptides, are characterized because of their broad range of biological activities, such as being mainly antimicrobials, but also antitumoral compounds, antivirals, siderophores, etc. [67,68,69,70]. The same fact happens with type III polyketides, in which we also found interesting activities [54,71,72]. In addition, carotenoids (terpenes) are also used in the pharmaceutical and food industries because of their antioxidant activities or colorant properties [73,74].
Thus, in this study we found an interesting genetic potential in the genome of M. brassicacearum CDVBN77T to synthesize enzymes and secondary metabolites. Moreover, we detected in vitro the production of some of the predicted enzymes and metabolites. Nevertheless, the purification of such gene products and the determination of their specific mechanisms of action in addition to the conditions of pH and temperature in which the molecules are active are required in order to determine the possible industrial interest of those substances.

5. Description of Microvirga brassicacearum sp. nov.

Microvirga brassicacearum (bras.si.ca.ce.a.rum. M.L. fem. pl. gen. n. brassicacearum of the Brassicaceae, referring to its isolation from the rhizoplane of plants belonging to the genus Brassica). Cells are rod-shaped, 1.2-1.5 µm in length and 0.7-0.9 µm in width, and motile by means of a polar flagellum. In 869(1/10) medium, colonies are transparent, circular, and flat, with an average size of 0.1–0.4 mm in diameter after seven days of growth at 28 °C in R2A medium. The temperature growth ranges between 12 and 37 °C, with an optimum of 28 °C. The growth at different pH ranges occurs between 6 and 10 with an optimum of 7. It grows between 0 and 1.5% NaCl in 869(1/10) liquid medium. Catalase and oxidase positive. The main polar lipids are phosphatidylcholine and phosphatidylethanolamine. Ubiquinone-10 (Q-10) is the major respiratory quinone and C19:0 cyclo ω8c and Summed Feature 8 are the main fatty acids. Results obtained in the API 20NE system indicate that the strain hydrolyzes aesculin, but it does not ferment D-glucose and does not hydrolyze arginine, urea, and gelatin. Reduction of nitrates to nitrites is positive. The assimilation of D-glucose, L-arabinose, D-mannitol, N-acetyl-glucosamine, D-maltose, potassium gluconate, malic acid, and trisodium citrate is positive and that of D-mannose, capric acid, adipic acid, and phenylacetic acid is negative. Results obtained in the API ZYM system showed activity in the enzymes alkaline phosphatase, esterase (C 4), esterase lipase (C 8), leucine arylamidase, trypsin, acid phosphatase, and naphtol-AS-BI-phosphohydrolase, but activity was not shown in lipase (C14), valine arylamidase, cysteine arylamidase, α-chymotrypsin, α-galactosidase, β-galactosidase, β-glucuronidase, β-glucosidase, α-glucosidase, N-acetyl-β-glucosaminidase, α-mannosidase, and α-fucosidase.
The G+C base composition was 62.3 mol %. The type strain, CDVBN77T (= LMG 31419T= CECT 9905T), was isolated as an endophyte from Brassica napus roots in Castellanos de Villiquera (Spain).

Author Contributions

Conceptualization, P.G.F.; methodology, P.G.-F., A.J.-G., Z.S.-S., J.M.I.; software, P.G.-F., A.J.-G. and Z.S.-S.; validation, P.G.-F., A.J.-G. and Z.S.-S; formal analysis, P.G.-F., A.J.-G. and Z.S.-S.; investigation, P.G.-F., A.J.-G., Z.S.-S. and J.M.I.; resources, P.G.F., R.R. and P.F.M.; data curation, P.G.-F., A.J.-G. and Z.S.-S.; writing—original draft preparation, P.G.-F., A.J.-G. and Z.S.-S.; writing—review and editing, P.G.-F., A.J.-G. and Z.S.-S.; visualization, P.G.-F., A.J.-G. and Z.S.-S.; supervision, P.G.F.; project administration, P.G.F.; funding acquisition, P.G.F.

Funding

This research was funded by the European Union’s Horizon 2020 research and innovation programme under the grant number 750795.

Acknowledgments

Authors thank the European Union’s Horizon 2020 research and innovation programme for the research funding received by P.G.-F. A.J.-G. thanks the Central Spanish Government for an FPU predoctoral grant and Z.S.-S. thanks the Junta de Castilla y Leon, Spanish Regional Government, for his predoctoral grant.

Conflicts of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Locey, K.J.; Lennon, J.T. Scaling laws predict global microbial diversity. Proc. Natl. Acad. Sci. USA 2016, 113, 5970–5975. [Google Scholar] [CrossRef] [PubMed]
  2. Jongsik, C.; Oren, A.; Ventosa, A.; Christensen, H.; Ruiz, D.; Da Costa, M.; Rooney, A.P.; Yi, H.; Wei, X.; de Meyer, S.; et al. Proposed minimal standards for the use of genome data for the taxonomy of prokaryotes. Int. J. Syst. Evol. Microbiol. 2018, 68, 461–466. [Google Scholar]
  3. Auch, A.F.; von Jan, M.; Klenk, H.P.; Göker, M. Digital DNA-DNA hybridization for microbial species delineation by means of genome-to-genome sequence comparison. Stand. Genom. Sci. 2010, 2, 117–134. [Google Scholar]
  4. López-Mondéjar, R.; Kostovčík, M.; Lladó, S.; Carro, L.; García-Fraile, P. Exploring the Plant Microbiome Through Multi-omics Approaches. Probiotics Agroecosystem 2017, 233–268. [Google Scholar]
  5. Saati-Santamaría, Z.; López-Mondéjar, R.; Jiménez-Gómez, A.; Díez-Méndez, A.; Větrovský, T.; Igual, J.M.; Velázquez, E.; Kolarik, M.; Rivas, R.; García-Fraile, P. Discovery of phloeophagus beetles as a source of Pseudomonas strains that produce potentially new bioactive substances and description of Pseudomonas bohemica sp. nov. Front. Microbiol. 2018, 9. [Google Scholar] [CrossRef] [PubMed]
  6. Fabryová, A.; Kostovčík, M.; Díez-Méndez, A.; Jiménez-Gómez, A.; Celador-Lera, L.; Saati-Santamaría, Z.; Sechovcová, H.; Menéndez, E.; Kolarik, M.; García-Fraile, P. On the bright side of a forest pest-the metabolic potential of bark beetles’ bacterial associates. Sci. Total Environ. 2018, 619, 9–17. [Google Scholar] [CrossRef]
  7. Gopal, M.; Gupta, A. Microbiome selection could spur next-generation plant breeding strategies. Front. Microbiol. 2016, 7, 1971. [Google Scholar] [CrossRef]
  8. Menéndez, E.; Garcia-Fraile, P. Plant probiotic bacteria: Solutions to feed the world. Aims Microbiol. 2017, 3, 502–524. [Google Scholar] [CrossRef]
  9. Caputo, A.; Lagier, J.C.; Azza, S.; Robert, C.; Mouelhi, D.; Fournier, P.E.; Raoult, D. Microvirga massiliensis sp. nov., the human commensal with the largest genome. Microbiol. Open 2016, 5, 307–322. [Google Scholar] [CrossRef]
  10. Weon, H.Y.; Kwon, S.W.; Son, J.A.; Jo, E.H.; Kim, S.J.; Kim, Y.S.; Kim, B.Y.; Ka, J.O. Description of Microvirga aerophila sp. nov. and Microvirga aerilata sp. nov., isolated from air, reclassification of Balneimonas flocculans Takeda et al. 2004 as Microvirga flocculans comb. nov. and emended description of the genus Microvirga. Int. J. Syst. Evol. Microbiol. 2010, 60, 2596–2600. [Google Scholar] [CrossRef]
  11. Kanso, S.; Patel, B.K. Microvirga subterranea gen. nov., sp. nov., a moderate thermophile from a deep subsurface Australian thermal aquifer. Int. J. Syst. Evol. Microbiol. 2003, 53, 401–406. [Google Scholar] [CrossRef] [PubMed]
  12. Zhang, J.; Song, F.; Xin, Y.H.; Zhang, J.; Fang, C. Microvirga guangxiensis sp. nov., a novel alphaproteobacterium from soil, and emended description of the genus Microvirga. Int. J. Syst. Evol. Microbiol. 2009, 59, 1997–2001. [Google Scholar] [CrossRef] [PubMed]
  13. Amin, A.; Ahmed, I.; Habib, N.; Abbas, S.; Hasan, F.; Xiao, M.; Hozzein, W.N.; Li, W.J. Microvirga pakistanensis sp. nov., a novel bacterium isolated from desert soil of Cholistan, Pakistan. Arch. Microbiol. 2016, 198, 933–939. [Google Scholar] [CrossRef] [PubMed]
  14. Dahal, R.H.; Kim, J. Microvirga soli sp. nov., an alphaproteobacterium isolated from soil. Int. J. Syst. Evol. Microbiol. 2017, 67, 127–132. [Google Scholar] [PubMed]
  15. Tapase, S.R.; Mawlankar, R.B.; Sundharam, S.S.; Krishnamurthi, S.; Dastager, S.G.; Kodam, K.M. Microvirga indica sp. nov., an arsenite-oxidizing Alphaproteobacterium, isolated from metal industry waste soil. Int. J. Syst. Evol. Microbiol. 2017, 67, 3525–3531. [Google Scholar] [CrossRef] [PubMed]
  16. Veyisoglu, A.; Tatar, D.; Saygin, H.; Inan, K.; Cetin, D.; Guven, K.; Tuncer, M.; Sahin, N. Microvirga makkahensis sp. nov., and Microvirga arabica sp. nov., isolated from sandy arid soil. Antonie Van Leeuwenhoek 2016, 109, 287–296. [Google Scholar] [CrossRef] [PubMed]
  17. Zhang, X.J.; Zhang, J.; Yao, Q.; Zhu, H.H. Microvirga flavescens sp. nov., a novel bacterium isolated from forest soil and emended description of the genus Microvirga. Int. J. Syst. Evol. Microbiol. 2019, 69, 667–671. [Google Scholar] [CrossRef]
  18. Ardley, J.K.; Parker, M.A.; De Meyer, S.E.; Trengove, R.D.; O’Hara, G.W.; Reeve, W.G.; Yates, R.J.; Dilworth, M.J.; Willems, A.; Howieson, J.G. Microvirga lupini sp. nov., Microvirga lotononidis sp. nov., and Microvirga zambiensis sp. nov. are Alphaproteobacterial root nodule bacteria that specifically nodulate and fix nitrogen with geographically and taxonomically separate legume hosts. Int. J. Syst. Evol. Microbiol. 2012, 62, 2579–2588. [Google Scholar] [CrossRef]
  19. Safronova, V.I.; Kuznetsova, I.G.; Sazanova, A.L.; Belimov, A.A.; Andronov, E.E.; Chirak, E.R.; Osledkin, Y.S.; Onishchuk, O.P.; Kurchak, O.N.; Shaposhnikov, A.I.; et al. Microvirga ossetica sp. nov., a species of rhizobia isolated from root nodules of the legume species Vicia alpestris Steven. Int. J. Syst. Evol. Microbiol. 2017, 67, 94–100. [Google Scholar]
  20. Radl, V.; Simões-Araújo, J.L.; Leite, J.; Passos, S.R.; Martins, L.M.V.; Xavier, G.R.; Rumjanek, N.G.; Baldani, J.I.; Zilli, J.E. Microvirga vignae sp. nov., a root nodule symbiotic bacterium isolated from cowpea grown in semi-arid Brazil. Int. J. Syst. Evol. Microbiol. 2017, 64, 725–730. [Google Scholar] [CrossRef]
  21. Samrot, A.V.; Rio, A.J.; Kumar, S.S.; Samanvitha, S.K. Bioprospecting studies of pigmenting Pseudomonas aeruginosa SU-1, Microvirga aerilata SU14 and Bacillus megaterium SU15 isolated from garden soil. Biocatal. Agric. Biotechnol. 2017, 11, 330–337. [Google Scholar] [CrossRef]
  22. Jiménez-Gómez, A.; Saati-Santamaría, Z.; Menéndez, E.; Rivas, R.; Mateos, P.F.; Velázquez, E.; García-Fraile, P. Analysis of the biodiversity of Brassica napus bacterial endophytes and selection of potential efficient biofertilizers for rapeseed crops. under review. Front. Microbiol.
  23. Altschul, S.F.; Madden, T.L.; Schäffer, A.A.; Zhang, J.; Zhang, Z.; Miller, W.; Lipman, D.J. Gapped BLAST and PSI-BLAST: A new generation of protein database search programs. Nucleic Acids Res. 1997, 25, 3389–3402. [Google Scholar] [CrossRef] [PubMed]
  24. Chun, J.; Lee, J.H.; Jung, Y.; Kim, M.; Kim, S.; Kim, B.K.; Lim, Y.W. EzTaxon: A web-based tool for the identification of prokaryotes based on 16S ribosomal RNA gene sequences. Int. J. Syst. Evol. Microbiol. 2007, 57, 2259–2261. [Google Scholar] [CrossRef] [PubMed]
  25. Zerbino, D.R.; Birney, E. Velvet: Algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 2008, 18, 821–829. [Google Scholar] [CrossRef] [PubMed]
  26. Aziz, R.K.; Bartels, D.; Best, A.A.; DeJongh, M.; Disz, T.; Edwards, R.A.; Meyer, F. The RAST Server: Rapid annotations using subsystems technology. BMC Genom. 2008, 9, 75. [Google Scholar] [CrossRef] [PubMed]
  27. Kanehisa, M.; Sato, Y.; Morishima, K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J. Mol. Biol. 2016, 428, 726–731. [Google Scholar] [CrossRef]
  28. Zhang, H.; Yohe, T.; Huang, L.; Entwistle, S.; Wu, P.; Yang, Z.; Yin, Y. dbCAN2: a meta server for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 2018, 46, 95–101. [Google Scholar]
  29. Blin, K.; Shaw, S.; Steinke, K.; Villebro, R.; Ziemert, N.; Lee, S.Y.; Weber, T. antiSMASH 5.0: Updates to the secondary metabolite genome mining pipeline. Nucleic Acids Res. 2019, 47, 81–87. [Google Scholar] [CrossRef]
  30. Kumar, S.; Stecher, G.; Tamura, K. MEGA7: Molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol. Biol. Evol. 2016, 33, 1870–1874. [Google Scholar] [CrossRef]
  31. Larkin, M.A.; Blackshields, G.; Brown, N.P.; Chenna, R.; McGettigan, P.A.; McWilliam, H.; Valentin, F.; Wallace, I.M.; Wilm, A.; Lopez, R.; et al. Clustal W and Clustal X version 2.0. Bioinformatics 2017, 23, 2947–2948. [Google Scholar] [CrossRef] [PubMed]
  32. Kimura, M. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. Mol. Biol. Evol. 1980, 16, 111–120. [Google Scholar] [CrossRef] [PubMed]
  33. Saitou, N.; Nei, M. The neighbor-joining method: A new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 1987, 4, 406–425. [Google Scholar] [PubMed]
  34. Menéndez, E.; Ramírez-Bahena, M.H.; Fabryová, A.; Igual, J.M.; Benada, O.; Mateos, P.F.; Peix, A.; Kolařík, M.; García-Fraile, P. Pseudomonas coleopterorum sp. nov., a cellulase-producing bacterium isolated from the bark beetle Hylesinus fraxini. Int. J. Syst. Evol. Microbiol. 2015, 65, 2852–2858. [Google Scholar]
  35. Lladó, S.; Benada, O.; Cajthaml, T.; Baldrian, P.; García-Fraile, P. Silvibacterium bohemicum gen. nov. sp. nov., an acidobacterium isolated from coniferous soil in the Bohemian Forest National Park. Syst. Appl. Microbiol. 2016, 39, 14–19. [Google Scholar]
  36. Doetsch, R.N. Determinative methods of light microscopy. Man. Meth. Gen. Bact. 1981, 21–33. [Google Scholar]
  37. Schwyn, B.; Neilands, J.B. Universal chemical assay for the detection and determination of siderophores. Anal. Biochem. 1987, 160, 47–56. [Google Scholar] [CrossRef]
  38. Alexander, D.B.; Zuberer, D.A. Use of Chrome Azurol S reagents to evaluate siderophore production by rhizosphere bacteria. Biol. Fertil. Soils 1991, 12, 39–45. [Google Scholar] [CrossRef]
  39. Pikovskaya, R.I. Mobilization of phosphorus in soil connection with the vital activity of some microbial species. Microbiologiya 1948, 17, 362–370. [Google Scholar]
  40. Robledo, M.; Rivera, L.; Jiménez-Zurdo, J.I.; Rivas, R.; Dazzo, F.; Velázquez, E.; Martínez-Molina, E.; Hirsch, A.; Mateos, P.F. Role of Rhizobium endoglucanase CelC2 in cellulose biosynthesis and biofilm formation on plant roots and abiotic surfaces. Microb. Cell Fact. 2012, 11, 125. [Google Scholar] [CrossRef]
  41. Richter, M.; Rosselló-Móra, R. Shifting the genomic gold standard for the prokaryotic species definition. Proc. Natl. Acad. Sci. USA 2009, 106, 19126–19131. [Google Scholar] [CrossRef] [PubMed]
  42. Meier-Kolthoff, J.P.; Auch, A.F.; Klenk, H.P.; Göker, M. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinform. 2013, 14, 60. [Google Scholar] [CrossRef] [PubMed]
  43. Kwak, Y.; Jung, B.K.; Shin, J.H. Complete genome sequence of Pseudomonas rhizosphaerae IH5T (= DSM 16299T), a phosphate-solubilizing rhizobacterium for bacterial biofertilizer. J. Biotechnol. 2015, 193, 137–138. [Google Scholar] [CrossRef] [PubMed]
  44. de Werra, P.; Péchy-Tarr, M.; Keel, C.; Maurhofer, M. Role of gluconic acid production in the regulation of biocontrol traits of Pseudomonas fluorescens CHA0. Appl. Environ. Microbiol. 2009, 75, 41624174. [Google Scholar] [CrossRef] [PubMed]
  45. Goldstein, A.H. Involvement of the quinoprotein glucose dehydrogenase in the solubilization of exogenous phosphates by gram-negative bacteria. In Phosphate in microorganisms: Cellular and Molecular biology; ASM Press: Washington, DC, USA, 1994; pp. 197–203. [Google Scholar]
  46. Etesami, H.; Emami, S.; Alikhani, H.A. Potassium solubilizing bacteria (KSB): Mechanisms, promotion of plant growth, and future prospects A review. J. Soil Sci. Plant Nutr. 2017, 17, 897–911. [Google Scholar] [CrossRef]
  47. Liu, W.; Wang, Q.; Hou, J.; Tu, C.; Luo, Y.; Christie, P. Whole genome analysis of halotolerant and alkalotolerant plant growth-promoting rhizobacterium Klebsiella sp. D5A. Sci. Rep. 2016, 6, 26710. [Google Scholar] [CrossRef]
  48. Epstein, W. The roles and regulation of potassium in bacteria. Prog. Nucleic Acid Res. 2003, 75, 293–320. [Google Scholar]
  49. Velázquez, E.; García-Fraile, P.; Ramírez-Bahena, M.H.; Rivas, R.; Martínez-Molina, E. Bacteria involved in nitrogen-fixing legume symbiosis: Current taxonomic perspective. Microbes Legume Improv. 2010, 1–25. [Google Scholar]
  50. Mateos, P.F.; Jimenez-Zurdo, J.I.; Chen, J.; Squartini, A.S.; Haack, S.K.; Martinez-Molina, E.; Hubbell, D.H.; Dazzo, F.B. Cell-associated pectinolytic and cellulolytic enzymes in Rhizobium leguminosarum biovar trifolii. Appl. Environ. Microbiol. 1992, 58, 1816–1822. [Google Scholar]
  51. Reed, J.W.; Walker, G.C. The exoD gene of Rhizobium meliloti encodes a novel function needed for alfalfa nodule invasion. J. Bacteriol. 1991, 173, 664–677. [Google Scholar] [CrossRef]
  52. Polissi, A.; Sperandeo, P. The lipopolysaccharide export pathway in Escherichia coli: Structure, organization and regulated assembly of the Lpt machinery. Mar. Drugs 2014, 12, 1023–1042. [Google Scholar] [CrossRef]
  53. Dong, H.; Zhang, Z.; Tang, X.; Paterson, N.G.; Dong, C. Structural and functional insights into the lipopolysaccharide ABC transporter LptB 2 FG. Nat. Commun. 2017, 8, 222. [Google Scholar] [CrossRef] [PubMed]
  54. Pradel, E.; Parker, C.T.; Schnaitman, C.A. Structures of the rfaB, rfaI, rfaJ, and rfaS genes of Escherichia coli K-12 and their roles in assembly of the lipopolysaccharide core. J. Bacteriol. 1992, 174, 4736–4745. [Google Scholar] [CrossRef] [PubMed]
  55. Fuqua, C.; Greenberg, E.P. Signalling: Listening in on bacteria: Acyl-homoserine lactone signalling. Nat. Rev. Mol. Cell Biol. 2002, 3, 685. [Google Scholar] [CrossRef] [PubMed]
  56. Yu, D.; Xu, F.; Zeng, J.; Zhan, J. Type III polyketide synthases in natural product biosynthesis. Iubmb Life 2012, 64, 285–295. [Google Scholar] [CrossRef] [PubMed]
  57. Rivas, R.; García-Fraile, P.; Mateos, P.F.; Martínez-Molina, E.; Velazquez, E. Paenibacillus cellulosilyticus sp. nov., a cellulolytic and xylanolytic bacterium isolated from the bract phyllosphere of Phoenix dactylifera. Int. J. Syst. Evol. Microbiol. 2006, 56, 2777–2781. [Google Scholar] [CrossRef] [PubMed]
  58. Rivas, R.; Garcia-Fraile, P.; Zurdo-Pineiro, J.L.; Mateos, P.F.; Martinez-Molina, E.; Bedmar, E.J.; Sánchez-Raya, J.; Velazquez, E. Saccharibacillus sacchari gen. nov., sp. nov., isolated from sugar cane. Int. J. Syst. Evol. Microbiol. 2008, 58, 1850–1854. [Google Scholar] [CrossRef]
  59. García-Fraile, P.; Velázquez, E.; Mateos, P.F.; Martínez-Molina, E.; Rivas, R. Cohnella phaseoli sp. nov., isolated from root nodules of Phaseolus coccineus in Spain, and emended description of the genus Cohnella. Int. J. Syst. Evol. Microbiol. 2008, 58, 1855–1859. [Google Scholar]
  60. Flores-Félix, J.D.; Carro, L.; Velázquez, E.; Valverde, Á.; Cerda-Castillo, E.; García-Fraile, P.; Rivas, R. Phyllobacterium endophyticum sp. nov., isolated from nodules of Phaseolus vulgaris. Int. J. Syst. Evol. Microbiol. 2013, 63, 821–826. [Google Scholar]
  61. Mansfield, S.D.; Mooney, C.; Saddler, J.N. Substrate and enzyme characteristics that limit cellulose hydrolysis. Biotechnol. Prog. 1999, 15, 804–816. [Google Scholar] [CrossRef]
  62. Sharma, B.; Sarkar, A.; Singh, P.; Singh, R.P. Agricultural utilization of biosolids: A review on potential effects on soil and plant grown. Waste Manag. 2017, 64, 117–132. [Google Scholar] [CrossRef]
  63. Menéndez, E.; García-Fraile, P.; Rivas, R. Biotechnological applications of bacterial cellulases. AIMS Bioeng. 2015, 2, 163–182. [Google Scholar] [CrossRef]
  64. Collin, T.; Gerday, C.; Feller, G. Xylanase, xylanase families and extremophilic xylanase. FEMS Microbiol. Rev. 2005, 29, 3–23. [Google Scholar] [CrossRef] [PubMed]
  65. Yadav, V.; Yadav, P.K.; Yadav, S.; Yadav, K.D.S. α-L-Rhamnosidase: A review. Process Biochem. 2010, 45, 1226–1235. [Google Scholar] [CrossRef]
  66. Xavier, J.R.; Ramana, K.V.; Sharma, R.K. β-galactosidase: Biotechnological applications in food processing. J. Food Biochem. 2018, 42, e12564. [Google Scholar] [CrossRef]
  67. Sieber, S.A.; Marahiel, M.A. Learning from nature’s drug factories: Nonribosomal synthesis of macrocyclic peptides. J. Bacteriol. 2003, 185, 7036–7043. [Google Scholar] [CrossRef]
  68. Finking, R.; Marahiel, M.A. Biosynthesis of nonribosomal peptides. Annu. Rev. Microbiol. 2004, 58, 453–488. [Google Scholar] [CrossRef]
  69. Felnagle, E.A.; Jackson, E.E.; Chan, Y.A.; Podevels, A.M.; Berti, A.D.; McMahon, M.D.; Thomas, M.G. Nonribosomal peptide synthetases involved in the production of medically relevant natural products. Mol. Pharm. 2008, 5, 191–211. [Google Scholar] [CrossRef]
  70. Agrawal, S.; Acharya, D.; Adholeya, A.; Barrow, C.J.; Deshmukh, S.K. Nonribosomal peptides from marine microbes and their antimicrobial and anticancer potential. Front. Pharm. 2017, 8, 828. [Google Scholar] [CrossRef]
  71. Gross, F.; Luniak, N.; Perlova, O.; Gaitatzis, N.; Jenke-Kodama, H.; Gerth, K.; Müller, R. Bacterial type III polyketide synthases: Phylogenetic analysis and potential for the production of novel secondary metabolites by heterologous expression in pseudomonads. Arch. Microbiol. 2006, 185, 28–38. [Google Scholar] [CrossRef]
  72. Katsuyama, Y.; Ohnishi, Y. Type III polyketide synthases in microorganisms. Methods Enzymol. 2012, 515, 359–377. [Google Scholar]
  73. Cardoso, L.A.; Karp, S.G.; Vendruscolo, F.; Kanno, K.Y.; Zoz, L.I.; Carvalho, J.C. Biotechnological production of carotenoids and their applications in food and pharmaceutical products. Carotenoids 2017, 125. [Google Scholar]
  74. Gateau, H.; Solymosi, K.; Marchand, J.; Schoefs, B. Carotenoids of microalgae used in food industry and medicine. Mini Rev. Med. Chem. 2017, 17, 1140–1172. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Neighbor-joining phylogenetic tree based on the nearly complete 16S rRNA gene sequences of all species classified within the genus Microvirga and the species Phylobacterium loti, which was included as an outgroup. The numbers are bootstrap values indicating the significance of the branches calculated as a percentage for 1000 subsets. Bar: 1 nt substitutions per 100 nt. Accession numbers of the sequences are indicated in parentheses.
Figure 1. Neighbor-joining phylogenetic tree based on the nearly complete 16S rRNA gene sequences of all species classified within the genus Microvirga and the species Phylobacterium loti, which was included as an outgroup. The numbers are bootstrap values indicating the significance of the branches calculated as a percentage for 1000 subsets. Bar: 1 nt substitutions per 100 nt. Accession numbers of the sequences are indicated in parentheses.
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Figure 2. Electron TEM micrograph showing bacterial shape and size and the flagellum of Microvirga brassicacearum CDVBN77T.
Figure 2. Electron TEM micrograph showing bacterial shape and size and the flagellum of Microvirga brassicacearum CDVBN77T.
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Table 1. Substrates for enzymatic enzymes.
Table 1. Substrates for enzymatic enzymes.
SubstrateEnzyme Assayed
PNP-α-L-arabinopyranosideα-L-arabinosidase
PNP-β-L-arabinopyranosideβ-L-arabinosidase
PNP-β-D-cellobiosideCellobiohydrolase
PNP-phosphate (at pH 5.0)Phosphatase
PNP-phosphate (at pH 7.0)Phosphatase
PNP-phosphate (at pH 8.5)Phosphatase
PNP-bis-phosphate (at pH 7)Bisphosphatase
PNP-bisphosphate (at pH 8.5)Bisphosphatase
PNP-α-L-fucopyranosideα-L-fucosidase
PNP-β-D-fucopyranosideβ-glucosidase
PNP-α-D-galactopyranosideα-galactosidase
PNP-β-D-galactopyranosideβ-galactosidase
PNP-β-D-galacturonideβ-galacturonidase
PNP-α-D-glucopyranosideα-glucosidase
PNP-β-D-glucopyranosideβ-glucosidase
PNP-β-D-glucuronideβ-glucuronidase
PNP-β-D-lactopyranosideβ-lactosidase
PNP-α-D-mannopyranosideα-mannosidase
PNP-β-D-mannopyranosideβ-mannosidase
PNP-α-L-rhamnopyranosideα-rhamnosidase
PNP-N-thio-β-D-glucopyranosideβ-glucosidase
PNP-α-D-xylopyranosideα-xylosidase
PNP-β-L-xylopyranosideβ-xylosidase
Table 2. Genome properties of Microvirga brassicacearum CDVBN77T.
Table 2. Genome properties of Microvirga brassicacearum CDVBN77T.
AttributesValue
Genome size (bp)5,221,427
G+C content (%)62.3
N50 value130,073
L50 value12
Number of contigs (with PEGs)88
Number of subsystems335
Number of coding sequences5,244
Number of RNAs51
Number of genes related to:
   Cofactors, vitamins, prosthetic groups, pigments151
   Cell wall and capsule45
   Virulence, disease, and defense55
   Potassium metabolism8
   Miscellaneous26
   Phages, prophages, transposable elements, plasmids16
   Membrane transport179
   Iron acquisition and metabolism10
   RNA metabolism41
   Nucleosides and nucleotides96
   Protein metabolism187
   Motility and chemotaxis16
   Regulation and cell signaling47
   Secondary metabolism6
   DNA metabolism94
   Fatty acids, lipids, and isoprenoids109
   Nitrogen metabolism39
   Dormancy and sporulation1
   Respiration109
   Stress response66
   Metabolism of aromatic compounds56
   Amino acids and derivatives367
   Sulfur metabolism42
   Phosphorus metabolism39
   Carbohydrates267
Table 3. Predicted gene modules for carbohydrate-active enzymes (CAZymes) families in the genome of Microvirga brassicacearum CDVBN77T.
Table 3. Predicted gene modules for carbohydrate-active enzymes (CAZymes) families in the genome of Microvirga brassicacearum CDVBN77T.
CAZyme FamilyGene CountKnown CAZyme Activities
GHs
15β-glucosidase (EC 3.2.1.21); β-galactosidase (EC 3.2.1.23); β-mannosidase (EC 3.2.1.25); β-glucuronidase (EC 3.2.1.31); β-xylosidase (EC 3.2.1.37); β-D-fucosidase (EC 3.2.1.38); exo-β-1,4-glucanase (EC 3.2.1.74); 6-phospho-β-galactosidase (EC 3.2.1.85); and others
22β-galactosidase (EC 3.2.1.23); β-mannosidase (EC 3.2.1.25); β-glucuronidase (EC 3.2.1.31); α-L-arabinofuranosidase (EC 3.2.1.55); exo-β-glucosaminidase (EC 3.2.1.165); α-L-arabinopyranosidase (EC 3.2.1.-); β-galacturonidase (EC 3.2.1.-); β-xylosidase (EC 3.2.1.37)
32β-glucosidase (EC 3.2.1.21); xylan 1,4-β-xylosidase (EC 3.2.1.37); β-glucosylceramidase (EC 3.2.1.45); β-N-acetylhexosaminidase (EC 3.2.1.52); α-L-arabinofuranosidase (EC 3.2.1.55); glucan 1,3-β-glucosidase (EC 3.2.1.58); glucan 1,4-β-glucosidase (EC 3.2.1.74); and others
151glucoamylase (EC 3.2.1.3); glucodextranase (EC 3.2.1.70); α,α-trehalase (EC 3.2.1.28); dextran dextrinase (EC 2.4.1.2)
163xyloglucan:xyloglucosyltransferase (EC 2.4.1.207); keratan-sulfate endo-1,4-β-galactosidase (EC 3.2.1.103); endo-1,3-β-glucanase (EC 3.2.1.39); endo-1,3(4)-β-glucanase (EC 3.2.1.6); licheninase (EC 3.2.1.73); and others
233lysozyme type G (EC 3.2.1.17); peptidoglycan lyase (EC 4.2.2.1), also known in the literature as peptidoglycan lytic transglycosylase; chitinase (EC 3.2.1.14)
251lysozyme (EC 3.2.1.17)
313α-glucosidase (EC 3.2.1.20); α-galactosidase (EC 3.2.1.22); α-mannosidase (EC 3.2.1.24); α-1,3-glucosidase (EC 3.2.1.84); sucrase-isomaltase (EC 3.2.1.48); α-xylosidase (EC 3.2.1.177); α-glucan lyase (EC 4.2.2.13); and others
631α-glucosidase (EC 3.2.1.106); α-1,3-glucosidase (EC 3.2.1.84); α-glucosidase (EC 3.2.1.20); mannosylglycerate α-mannosidase / mannosylglycerate hydrolase (EC 3.2.1.170)
1021peptidoglycan lytic transglycosylase (EC 3.2.1.-)
1033peptidoglycan lytic transglycosylase (EC 3.2.1.-)
1051unsaturated rhamnogalacturonyl hydrolase (EC 3.2.1.172); d-4,5-unsaturated β-glucuronyl hydrolase (EC 3.2.1.-); d-4,5-unsaturated α-galacturonidase (EC 3.2.1.-)
1081N-acetylmuramidase (EC 3.2.1.17)
1092α-N-acetylgalactosaminidase (EC 3.2.1.49)
1131β-mannanase (EC 3.2.1.78)
PLs
91pectate lyase (EC 4.2.2.2); exopolygalacturonate lyase (EC 4.2.2.9); thiopeptidoglycan lyase (EC 4.2.2.-)
201endo-β-1,4-glucuronan lyase (EC 4.2.2.14)
GTs
11UDP-glucuronosyltransferase (EC 2.4.1.17); zeatin O-β-xylosyltransferase (EC 2.4.2.40); 2-hydroxyacylsphingosine 1-β-galactosyltransferase (EC 2.4.1.45); N-acylsphingosine galactosyltransferase (EC 2.4.1.47); and others
211cellulose synthase (EC 2.4.1.12); chitin synthase (EC 2.4.1.16); dolichyl-phosphate β-D-mannosyltransferase (EC 2.4.1.83); dolichyl-phosphate β-glucosyltransferase (EC 2.4.1.117); N-acetylglucosaminyltransferase (EC 2.4.1.-); and others
419sucrose synthase (EC 2.4.1.13); sucrose-phosphate synthase (EC 2.4.1.14); α-glucosyltransferase (EC 2.4.1.52); lipopolysaccharide N-acetylglucosaminyltransferase (EC 2.4.1.56); phosphatidylinositol α-mannosyltransferase (EC 2.4.1.57); and others
191lipid-A-disaccharide synthase (EC 2.4.1.182)
201α,α-trehalose-phosphate synthase [UDP-forming] (EC 2.4.1.15); glucosylglycerol-phosphate synthase (EC 2.4.1.213); trehalose-6-P phosphatase (EC 3.1.3.12); [retaining] GDP-valeniol: validamine 7-phosphate valeniolyltransferase (EC 2.-.-.-)
271polypeptide α-N-acetylgalactosaminyltransferase (EC 2.4.1.41)
2821,2-diacylglycerol 3-β-galactosyltransferase (EC 2.4.1.46); 1,2-diacylglycerol 3-β-glucosyltransferase (EC 2.4.1.157); UDP-GlcNAc: Und-PP-MurAc-pentapeptide β-N-acetylglucosaminyltransferase (EC 2.4.1.227); digalactosyldiacylglycerol synthase (EC 2.4.1.241)
301CMP-β-KDO: α-3-deoxy-D-manno-octulosonic-acid (KDO) transferase (EC 2.4.99.-)
516murein polymerase (EC 2.4.1.129)
831undecaprenyl phosphate-α-L-Ara4N: 4-amino-4-deoxy-β-L-arabinosyltransferase (EC 2.4.2.43); dodecaprenyl phosphate-β-galacturonic acid: lipopolysaccharide core α-galacturonosyl transferase (EC 2.4.1.-)
942GDP-Man: GlcA-β-1,2-Man-α-1,3-Glc-β-1,4-Glc-α-1-PP-undecaprenol β-1,4-mannosyltransferase (EC 2.4.1.251)
CEs
14acetyl xylan esterase (EC 3.1.1.72); cinnamoyl esterase (EC 3.1.1.-); feruloyl esterase (EC 3.1.1.73); carboxylesterase (EC 3.1.1.1); S-formylglutathione hydrolase (EC 3.1.2.12); diacylglycerol O-acyltransferase (EC 2.3.1.20); trehalose 6-O-mycolyltransferase (EC 2.3.1.122)
48acetyl xylan esterase (EC 3.1.1.72); chitin deacetylase (EC 3.5.1.41); chitooligosaccharide deacetylase (EC 3.5.1.-); peptidoglycan GlcNAc deacetylase (EC 3.5.1.-); peptidoglycan N-acetylmuramic acid deacetylase (EC 3.5.1.-)
92N-acetylglucosamine 6-phosphate deacetylase (EC 3.5.1.25); N-acetylglucosamine 6-phosphate deacetylase (EC 3.5.1.80)
106arylesterase (EC 3.1.1.-); carboxyl esterase (EC 3.1.1.3); acetylcholinesterase (EC 3.1.1.7); cholinesterase (EC 3.1.1.8); sterol esterase (EC 3.1.1.13); brefeldin A esterase (EC 3.1.1.-)
111UDP-3-0-acyl N-acetylglucosamine deacetylase (EC 3.5.1.-)
141N-acetyl-1-D-myo-inosityl-2-amino-2-deoxy-α-D-glucopyranoside deacetylase (EC 3.5.1.89); diacetylchitobiose deacetylase (EC 3.5.1.-); mycothiol S-conjugate amidase (EC 3.5.1.-)
AAs
35cellobiose dehydrogenase (EC 1.1.99.18); glucose 1-oxidase (EC 1.1.3.4); aryl alcohol oxidase (EC 1.1.3.7); alcohol oxidase (EC 1.1.3.13); pyranose oxidase (EC 1.1.3.10)
46vanillyl-alcohol oxidase (EC 1.1.3.38)
611,4-benzoquinone reductase (EC 1.6.5.6)
72glucooligosaccharide oxidase (EC 1.1.3.-); chitooligosaccharide oxidase (EC 1.1.3.-)
121pyrroloquinoline quinone-dependent oxidoreductase
Table 4. Cellular fatty acid composition (%) of Microvirga brassicacearum CDVBN77T (data from this study) and its closest related species M. flavescens c27j1T (data from Zhang et al. [17]) and M. aerophila DSM 21344T (data from Weon et al. [10]), as well as for the type species of the genus M. subterranea DSM 14364T (data from Kanso and Patel [11]). Strains: 1, M. brassicacearum CDVBN77T; 2, M. flavescens c27j1T; 3, M. aerophila DSM 21344T; 4, M. subterranea DSM 14364T.
Table 4. Cellular fatty acid composition (%) of Microvirga brassicacearum CDVBN77T (data from this study) and its closest related species M. flavescens c27j1T (data from Zhang et al. [17]) and M. aerophila DSM 21344T (data from Weon et al. [10]), as well as for the type species of the genus M. subterranea DSM 14364T (data from Kanso and Patel [11]). Strains: 1, M. brassicacearum CDVBN77T; 2, M. flavescens c27j1T; 3, M. aerophila DSM 21344T; 4, M. subterranea DSM 14364T.
Fatty Acid1234
C16:09.24.86.67.6
C17:0 tr7.5
C18:06.12.03.15.5
C17:0 cyclo3.83.52.1tr
19:0 cyclo ω8c24.357.711.827.9
C20:2 ω6,9c 1.1tr1.1
11-Methyl C18:1 ω7c4.21.5tr1.5
C18:0 3-OH1.72.11.11.7
Summed feature 24.55.01.43.2
Summed feature 34.51.15.21.1
Summed feature 839.318.564.838.5
The values are percentages of the total fatty acids. The values under 1% for all of the strains are not included. tr: traces, values under 1%. Summed feature 2: C12:0 aldehyde and/or unknown 10.9525. Summed feature 3: C16:1 ω7c and/or C16:1 ω6c. Summed feature 8: C18:1 ω7c and/or C18:1 ω6c.
Table 5. Phenotypic differences between Microvirga brassicacearum CDVBN77T (data from this study) and its closest related species M. flavescens c27j1T (data from Zhang et al. [17]) and M. aerophila DSM 21344T (data from Weon et al. [10]), as well as for the type species of the genus M. subterranea DSM 14364T (data from Kanso and Patel [11]) Strains: 1, M. brassicacearum CDVBN77T; 2, M. flavescens c27j1T; 3, M. aerophila DSM 21344T; 4, M. subterranea DSM 14364T. +, positive; w, weakly positive; -, negative.
Table 5. Phenotypic differences between Microvirga brassicacearum CDVBN77T (data from this study) and its closest related species M. flavescens c27j1T (data from Zhang et al. [17]) and M. aerophila DSM 21344T (data from Weon et al. [10]), as well as for the type species of the genus M. subterranea DSM 14364T (data from Kanso and Patel [11]) Strains: 1, M. brassicacearum CDVBN77T; 2, M. flavescens c27j1T; 3, M. aerophila DSM 21344T; 4, M. subterranea DSM 14364T. +, positive; w, weakly positive; -, negative.
Characteristic1234
Isolation sourcePlantSoilAirThermal aquifer
Colony colorWhiteFaint yellowLight pinkLight pink
Motility++
Oxidase+++
Nitrate reduction+++
Hydrolysis of:
Gelatin++
Aesculin+
Assimilation of:
D-Glucose++
L-Arabinose+++
Production of:
β-glucoronidase+
Esterase lipase (c8)+w++
Trypsin++w
pH range6–106–107–106–9
Salinity range (%)0–1.50–10–20–1
Temperature range (°C)12–3715–3710–3525–45
DNA G+C content (mol %)62.362.262.165.1
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